Search Results - squared multivariable linear regression algorithm

Optimizing Photovoltaic Arrays: A Novel Approach to Maximize Power Output in Varied Shading Patterns by Zaiba Ishrat, Ankur Gupta, Seema Nayak

“…). To extract the utmost energy from the SPS, the authors proposed an efficient hybrid algorithm integrating the advantages of machine learning and the classical algorithm fractional open circuit voltage (FOVA) to track the GPPP…”
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Can machine learning provide preoperative predictions of biological hemostasis after extracorporeal circulation for cardiac surgery? by Perduca, Vittorio, Bouaziz, Olivier, Zannis, Kostantinos, Beaussier, Marc, Untereiner, Olivier

“… learning algorithm, we trained and tested a variety of algorithms together with the super learning algorithm, a state…”
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Quantum clustering-based weighted linear programming support vector regression for multivariable nonlinear problem by Yu, Yanfang, Qian, Feng, Liu, Huimin

“… We present the v -linear programming support vector regression approach based on quantum clustering and weighted strategy to solve the multivariable nonlinear regression problem…”
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Multivariable Fractional Polynomials for lithium-ion batteries degradation models under dynamic conditions by Bertinelli Salucci, Clara, Bakdi, Azzeddine, Glad, Ingrid Kristine, Vanem, Erik, De Bin, Riccardo

“… Hence, it is crucial to implement fast and accurate algorithms for State of Health (SoH) monitoring on the Battery Management System…”
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Quantifying natural organic matter concentration in water from climatological parameters using different machine learning algorithms by Moradi, Sina, Agostino, Anthony, Gandomkar, Ziba, Kim, Seokhyeon, Hamilton, Lisa, Sharma, Ashish, Henderson, Rita, Leslie, Greg

“…) were selected from a large dataset to develop and train each machine learning model. The accuracy of the multivariable linear regression, support vector regression (SVR…”
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Application of Soft Computing Techniques for Predicting Thermal Conductivity of Rocks by Samaei, Masoud, Massalow, Timur, Abdolhosseinzadeh, Ali, Yagiz, Saffet, Sabri, Mohanad Muayad Sabri

“…Due to the different challenges in rock sampling and in measuring their thermal conductivity (TC) in the field and laboratory, the determination of the TC of…”
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A Machine Learning Approach to Predicting Case Duration for Robot-Assisted Surgery by Zhao, Beiqun, Waterman, Ruth S., Urman, Richard D., Gabriel, Rodney A.

“…: 1) multivariable linear regression, 2) ridge regression, 3) lasso regression, 4) random forest, 5) boosted regression tree…”
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Forecasting influenza-like illness trends in Cameroon using Google Search Data by Nsoesie, Elaine O., Oladeji, Olubusola, Abah, Aristide S. Abah, Ndeffo-Mbah, Martial L.

“…) regression, support vector machines (SVM) regression, multivariable linear regression and ARIMA models to forecast 2012 to 2018 trends of reported ILI cases in Cameroon, using Google searches for influenza symptoms, treatments, natural…”
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Revision total knee arthroplasty for arthrofibrosis improves range of motion by Rockov, Zachary A., Byrne, Connor T., Rezzadeh, Kevin T., Durst, Caleb R., Spitzer, Andrew I., Paiement, Guy D., Penenberg, Brad L., Rajaee, Sean S.

“… While treatment algorithms involve early physical therapy and manipulation under anaesthesia (MUA), some patients ultimately require revision TKA…”
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RFIS: regression-based fuzzy inference system by Wiktorowicz, Krzysztof

“… To determine their parameters, linear and nonlinear regressions are used. The linear regression is realized by the ridge regression and the nonlinear regression by the Levenberg–Marquardt algorithm…”
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Does Using Factor Analysis to Select Covariates in Mapping Algorithms Improve Predictive Accuracy? A Case of Mapping the Core 23-Item Women’s Health Questionnaire Onto the EQ-5D-5L and SF-6D by Kaambwa, B, de Lacey, S, Smith, C, Ratcliffe, J

“…OBJECTIVES: In addition to theoretical justifications, many statistical methods have been used for selecting covariates to include in algorithms mapping non-utility measures onto utilities…”
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Comparing supervised machine learning algorithms for the prediction of partial arterial pressure of oxygen during craniotomy by Gutmann, Andrea S., Mandl, Maximilian M., Rieder, Clemens, Hoechter, Dominik J., Dietz, Konstantin, Geisler, Benjamin P., Boulesteix, Anne-Laure, Tomasi, Roland, Hinske, Ludwig C.

“… . Six machine learning regression algorithms (gradient boosting, k-nearest neighbors, random forest, support vector, neural network, linear model with stochastic gradient descent…”
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POS0505 EVALUATING HEALTH UTILITIES BASED ON ASAS HEALTH INDEX IN SPONDYLOARTHRITIS: AN ANCILLARY ANALYSIS FROM THE ASAS-HI INTERNATIONAL VALIDATION STUDY by Calixto, O. J., Kiltz, U., Bautista-Molano, W., Boonen, A., Ivette, E., Baraliakos, X.

“…]. Recently an algorithm was computed to convert the ASAS HI scores into utility values from a general population perspective [2…”
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Hand bone loss in early rheumatoid arthritis during a methotrexate-based treat-to-target strategy with or without adalimumab—a substudy of the optimized treatment algorithm in early RA (OPERA) trial by Ørnbjerg, L. M., Østergaard, M., Jensen, T., Hørslev-Petersen, K., Stengaard-Pedersen, K., Junker, P., Ellingsen, T., Ahlquist, P., Lindegaard, H., Linauskas, A., Schlemmer, A., Dam, M. Y., Hansen, I., Lottenburger, T., Ammitzbøll, C. G., Jørgensen, A., Krintel, S. B., Raun, J., Hetland, M. L., Slot, Ole, Nielsen, Lars Kjær, Skjødt, Henrik, Majgaard, Ole, Lorenzen, Tove, Horn, Hans Christian, Kowalski, Marcin, Johansen, Inger Lauge, Pedersen, Peter Mosborg, Manilo, Natalia, Bliddal, Henning

“… Baseline characteristics and HBL 6months (0–6 months changes in DXR-BMD) were investigated as predictors of structural damage by univariate linear…”
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Multicenter External Validation and Comparison of Stone Scoring Systems in Predicting Outcomes After Percutaneous Nephrolithotomy by Tailly, Thomas O, Okhunov, Zhamshid, Nadeau, Brandon R, Huynh, Melissa Jessica, Labadie, Kevin, Akhavein, Arash, Violette, Philippe D, Olvera-Posada, Daniel, Alenezi, Husain, Amann, Justin, Bird, Vincent G, Landman, Jaime, Smith, Arthur D, Denstedt, John D, Razvi, Hassan

“…), complications, and length of stay (LOS). We performed chi-squared, t-test, logistic, linear, and Poisson regressions, as well as receiver operating characteristics…”
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Modeling of the oxygen aeration performance efficiency of gabion spillways by Srinivas, Rathod, Tiwari, N. K.

“… Besides, traditional equations, namely developed multivariable linear regression (MLR) and multivariable nonlinear regression (MNLR…”
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Prenatal exposure to ambient air pollutants and early infant growth and adiposity in the Southern California Mother’s Milk Study by Patterson, William B., Glasson, Jessica, Naik, Noopur, Jones, Roshonda B., Berger, Paige K., Plows, Jasmine F., Minor, Hilary A., Lurmann, Frederick, Goran, Michael I., Alderete, Tanya L.

“… ]; oxidative capacity [O x wt : redox-weighted oxidative potential of O 3 and NO 2 ]) was modeled by spatial interpolation of monitoring stations via an inverse distance-squared weighting (IDW2…”
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Validation of gestational age determination from ultrasound or a metabolic gestational age algorithm using exact date of conception in a cohort of newborns conceived using assisted reproduction technologies by Hawken, Steven, Olibris, Brieanne, Ducharme, Robin, Bota, A. Brianne, Murray, Jeffrey C., Potter, Beth K., Walker, Mark, Chakraborty, Pranesh, Wilson, Kumanan

“…Accurate estimates of gestational age in pregnancy are important for the provision of optimal care. Although current guidelines generally recommend estimating…”
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Mapping the Children’s Dermatology Life Quality Index Questionnaire to EQ-5D-Y-3L in Pediatric Patients With Atopic Dermatitis by Nazeha, Nuraini, Senanayake, Sameera, Cai, Yiying, Koh, Mark J.A., Bing, Su, Hong, Weiwei, Graves, Nicholas, Kularatna, Sanjeewa

“…) using 4 regression techniques: ordinary least squares, general linear regression, multivariable fractional polynomials, and beta regression…”
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A mathematical model for predicting glucose levels in critically-ill patients: the PIGnOLI model by Zhang, Zhongheng

“… Linear regression model fitting was employed. Retested blood glucose was used as the independent variable…”
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